System and method for presentation of media related to a context

ABSTRACT

A system and method for presentation of media related to a context. A request is received over a network from a requesting device for media related to a context, wherein the request comprises at least one criteria. A query is formulated based on the context criteria so as to search, via the network, for user profile data, social network data, spatial data, temporal data and topical data that is available via the network and relates to the context and to media files so as to identify at least one media file that is relevant to the context criteria. A playlist is assembled via the network containing a reference to the media files. The media files on the playlist are transmitted over the network to the requesting device.

This application includes material which is subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent disclosure, as it appears in thePatent and Trademark Office files or records, but otherwise reserves allcopyright rights whatsoever.

FIELD OF THE INVENTION

The present invention relates to systems and methods for selecting andpresenting media on a network and, more particularly, to systems andmethods for selecting and presenting media which relates to a specifictopic using, in part, data collected and stored by multiple devices on anetwork.

BACKGROUND OF THE INVENTION

A great deal of information is generated when people use electronicdevices, such as when people use mobile phones and cable set-top boxes.Such information, such as location, applications used, social network,physical and online locations visited, to name a few, could be used todeliver useful services and information to end users, and providecommercial opportunities to advertisers and retailers. However, most ofthis information is effectively abandoned due to deficiencies in the waysuch information can be captured. For example, and with respect to amobile phone, information is generally not gathered while the mobilephone is idle (i.e., not being used by a user). Other information, suchas presence of others in the immediate vicinity, time and frequency ofmessages to other users, and activities of a user's social network arealso not captured effectively.

SUMMARY OF THE INVENTION

In one embodiment, the invention is a method, a request is received overa network from a requesting device for media related to a context,wherein the request comprises at least one criteria. A query isformulated based on the context criteria so as to search, via thenetwork, for user profile data, social network data, spatial data,temporal data and topical data that is available via the network andrelates to the context and to media files so as to identify at least onemedia file that is relevant to the context criteria. A playlist isassembled via the network containing a reference to the media files. Themedia files on the playlist are transmitted over the network to therequesting device.

In another embodiment, the invention is a system. The system comprise: acontext entry module that enables entry of a request on a requestingdevice for media related to a context, wherein the request contains atleast one criteria; a query module that uses context criteria enteredthrough the context entry module to formulate a query based on thecontext criteria so as to search, via the network, for user profiledata, social network data, spatial data, temporal data and topical datathat is available via the network and relates to the context and tomedia files so as to identify at least one media file that is relevantto the context criteria; a playlist generation module that assemblesplaylists containing a reference to the at least one media file; and amedia delivery module that transmitting the media files on the playlistover a network to the requesting device.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of theinvention will be apparent from the following more particulardescription of preferred embodiments as illustrated in the accompanyingdrawings, in which reference characters refer to the same partsthroughout the various views. The drawings are not necessarily to scale,emphasis instead being placed upon illustrating principles of theinvention.

FIG. 1 illustrates relationships between real-world entities (RWE) andinformation objects (IO) on one embodiment of a W4 CommunicationsNetwork (W4 COMN.)

FIG. 2 illustrates metadata defining the relationships between RWEs andIOs on one embodiment of a W4 COMN.

FIG. 3 illustrates a conceptual model of one embodiment of a W4 COMN.

FIG. 4 illustrates the functional layers of one embodiment of the W4COMN architecture.

FIG. 5 illustrates the analysis components of one embodiment of a W4engine as shown in FIG. 2.

FIG. 6 illustrates one embodiment of a W4 engine showing differentcomponents within the sub-engines shown in FIG. 5.

FIG. 7 illustrates one embodiment of a data model showing how a networksuch as a W4 COMN can store media files and relate such files to RWEs,such as persons and places, and IOs, such as topics and other types ofmetadata.

FIG. 8 illustrates one embodiment of a process of how a networkcontaining temporal, spatial, and social network and topical data for aplurality of users, devices, and media, such as a W4 COMN, can be usedto enable customized music delivery for complex user contexts havingwho, where, when, and what criteria.

FIG. 9 further illustrates how the process illustrated in FIG. 8 can besupported by one embodiment of a W4 COMN or other network providingsimilar data and processing capabilities.

FIG. 10 illustrates the components of one embodiment of a context queryengine.

DETAILED DESCRIPTION

The present invention is described below with reference to blockdiagrams and operational illustrations of methods and devices to selectand present media related to a specific topic. It is understood thateach block of the block diagrams or operational illustrations, andcombinations of blocks in the block diagrams or operationalillustrations, can be implemented by means of analog or digital hardwareand computer program instructions.

These computer program instructions can be provided to a processor of agenrel purpose computer, special purpose computer, ASIC, or otherprogrammable data processing apparatus, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, implements the functions/acts specified inthe block diagrams or operational block or blocks.

In some alternate implementations, the functions/acts noted in theblocks can occur out of the order noted in the operationalillustrations. For example, two blocks shown in succession can in factbe executed substantially concurrently or the blocks can sometimes beexecuted in the reverse order, depending upon the functionality/actsinvolved.

For the purposes of this disclosure the term “server” should beunderstood to refer to a service point which provides processing,database, and communication facilities. By way of example, and notlimitation, the term “server” can refer to a single, physical processorwith associated communications and data storage and database facilities,or it can refer to a networked or clustered complex of processors andassociated network and storage devices, as well as operating softwareand one or more database systems and applications software which supportthe services provided by the server.

For the purposes of this disclosure the term “end user” or “user” shouldbe understood to refer to a consumer of data supplied by a dataprovider. By way of example, and not limitation, the term “end user” canrefer to a person who receives data provided by the data provider overthe Internet in a browser session, or can refer to an automated softwareapplication which receives the data and stores or processes the data.

For the purposes of this disclosure the term “media” and “media content”should be understood to refer to binary data which contains contentwhich can be of interest to an end user. By way of example, and notlimitation, the term “media” and “media content” can refer to multimediadata, such as video data or audio data, or any other form of datacapable of being transformed into a form perceivable by an end user.Such data can, furthermore, be encoded in any manner currently known, orwhich can be developed in the future, for specific purposes. By way ofexample, and not limitation, the data can be encrypted, compressed,and/or can contained embedded metadata.

For the purposes of this disclosure, a computer readable medium storescomputer data in machine readable form. By way of example, and notlimitation, a computer readable medium can comprise computer storagemedia and communication media. Computer storage media includes volatileand non-volatile, removable and non-removable media implemented in anymethod or technology for storage of information such ascomputer-readable instructions, data structures, program modules orother data. Computer storage media includes, but is not limited to, RAM,ROM, EPROM, EEPROM, flash memory or other solid-state memory technology,CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetictape, magnetic disk storage or other mass storage devices, or any othermedium which can be used to store the desired information and which canbe accessed by the computer.

For the purposes of this disclosure a module is a software, hardware, orfirmware (or combinations thereof) system, process or functionality, orcomponent thereof, that performs or facilitates the processes, features,and/or functions described herein (with or without human interaction oraugmentation). A module can include sub-modules. Software components ofa module may be stored on a computer readable medium. Modules may beintegral to one or more servers, or be loaded and executed by one ormore servers. One or more modules may grouped into an engine or anapplication.

Embodiments of the present invention utilize information provided by anetwork which is capable of providing data collected and stored bymultiple devices on a network. Such information may include, withoutlimitation, temporal information, spatial information, and userinformation relating to a specific user or hardware device. Userinformation may include, without limitation, user demographics, userpreferences, user social networks, and user behavior. One embodiment ofsuch a network is a W4 Communications Network.

A “W4 Communications Network” or W4 COMN, provides information relatedto the “Who, What, When and Where” of interactions within the network.In one embodiment, the W4 COMN is a collection of users, devices andprocesses that foster both synchronous and asynchronous communicationsbetween users and their proxies providing an instrumented network ofsensors providing data recognition and collection in real-worldenvironments about any subject, location, user or combination thereof.

In one embodiment, the W4 COMN can handle the routing/addressing,scheduling, filtering, prioritization, replying, forwarding, storing,deleting, privacy, transacting, triggering of a new message, propagatingchanges, transcoding and linking. Furthermore, these actions can beperformed on any communication channel accessible by the W4 COMN.

In one embodiment, the W4 COMN uses a data modeling strategy forcreating profiles for not only users and locations, but also any deviceon the network and any kind of user-defined data with user-specifiedconditions. Using Social, Spatial, Temporal and Logical data availableabout a specific user, topic or logical data object, every entity knownto the W4 COMN can be mapped and represented against all other knownentities and data objects in order to create both a micro graph forevery entity as well as a global graph that relates all known entitieswith one another. In one embodiment, such relationships between entitiesand data objects are stored in a global index within the W4 COMN.

In one embodiment, a W4 COMN network relates to what may be termed“real-world entities”, hereinafter referred to as RWEs. A RWE refers to,without limitation, a person, device, location, or other physical thingknown to a W4 COMN. In one embodiment, each RWE known to a W4 COMN isassigned a unique W4 identification number that identifies the RWEwithin the W4 COMN.

RWEs can interact with the network directly or through proxies, whichcan themselves be RWEs. Examples of RWEs that interact directly with theW4 COMN include any device such as a sensor, motor, or other piece ofhardware connected to the W4 COMN in order to receive or transmit dataor control signals. RWE may include all devices that can serve asnetwork nodes or generate, request and/or consume data in a networkedenvironment or that can be controlled through a network. Such devicesinclude any kind of “dumb” device purpose-designed to interact with anetwork (e.g., cell phones, cable television set top boxes, faxmachines, telephones, and radio frequency identification (RFID) tags,sensors, etc.).

Examples of RWEs that may use proxies to interact with W4 COMN networkinclude non-electronic entities including physical entities, such aspeople, locations (e.g., states, cities, houses, buildings, airports,roads, etc.) and things (e.g., animals, pets, livestock, gardens,physical objects, cars, airplanes, works of art, etc.), and intangibleentities such as business entities, legal entities, groups of people orsports teams. In addition, “smart” devices (e.g., computing devices suchas smart phones, smart set top boxes, smart cars that supportcommunication with other devices or networks, laptop computers, personalcomputers, server computers, satellites, etc.) may be considered RWEthat use proxies to interact with the network, where softwareapplications executing on the device that serve as the devices' proxies.

In one embodiment, a W4 COMN may allow associations between RWEs to bedetermined and tracked. For example, a given user (an RWE) can beassociated with any number and type of other RWEs including otherpeople, cell phones, smart credit cards, personal data assistants, emailand other communication service accounts, networked computers, smartappliances, set top boxes and receivers for cable television and othermedia services, and any other networked device. This association can bemade explicitly by the user, such as when the RWE is installed into theW4 COMN.

An example of this is the set up of a new cell phone, cable televisionservice or email account in which a user explicitly identifies an RWE(e.g., the user's phone for the cell phone service, the user's set topbox and/or a location for cable service, or a username and password forthe online service) as being directly associated with the user. Thisexplicit association can include the user identifying a specificrelationship between the user and the RWE (e.g., this is my device, thisis my home appliance, this person is my friend/father/son/etc., thisdevice is shared between me and other users, etc.). RWEs can also beimplicitly associated with a user based on a current situation. Forexample, a weather sensor on the W4 COMN can be implicitly associatedwith a user based on information indicating that the user lives or ispassing near the sensor's location.

In one embodiment, a W4 COMN network may additionally include what maybe termed “information-objects”, hereinafter referred to as IOs. Aninformation object (IO) is a logical object that may store, maintain,generate or otherwise provides data for use by RWEs and/or the W4 COMN.In one embodiment, data within in an IO can be revised by the act of anRWE An IO within in a W4 COMN can be provided a unique W4 identificationnumber that identifies the IO within the W4 COMN.

In one embodiment, IOs include passive objects such as communicationsignals (e.g., digital and analog telephone signals, streaming media andinterprocess communications), email messages, transaction records,virtual cards, event records (e.g., a data file identifying a time,possibly in combination with one or more RWEs such as users andlocations, that can further be associated with a knowntopic/activity/significance such as a concert, rally, meeting, sportingevent, etc.), recordings of phone calls, calendar entries, web pages,database entries, electronic media objects (e.g., media files containingsongs, videos, pictures, images, audio messages, phone calls, etc.),electronic files and associated metadata.

In one embodiment, IOs include any executing process or application thatconsumes or generates data such as an email communication application(such as OUTLOOK by MICROSOFT, or YAHOO! MAIL by YAHOO!), a calendaringapplication, a word processing application, an image editingapplication, a media player application, a weather monitoringapplication, a browser application and a web page server application.Such active IOs can or can not serve as a proxy for one or more RWEs.For example, voice communication software on a smart phone can serve asthe proxy for both the smart phone and for the owner of the smart phone.

In one embodiment, for every IO there are at least three classes ofassociated RWEs. The first is the RWE that owns or controls the IO,whether as the creator or a rights holder (e.g., an RWE with editingrights or use rights to the IO). The second is the RWE(s) that the IOrelates to, for example by containing information about the RWE or thatidentifies the RWE. The third are any RWEs that access the IO in orderto obtain data from the IO for some purpose.

Within the context of a W4 COMN, “available data” and “W4 data” meansdata that exists in an IO or data that can be collected from a known IOor RWE such as a deployed sensor. Within the context of a W4 COMN,“sensor” means any source of W4 data including PCs, phones, portable PCsor other wireless devices, household devices, cars, appliances, securityscanners, video surveillance, RFID tags in clothes, products andlocations, online data or any other source of information about areal-world user/topic/thing (RWE) or logic-basedagent/process/topic/thing (IO).

FIG. 1 illustrates one embodiment of relationships between RWEs and IOson a W4 COMN. A user 102 is a RWE provided with a unique network ID. Theuser 102 may be a human that communicates with the network using proxydevices 104, 106, 108, 110 associated with the user 102, all of whichare RWEs having a unique network ID. These proxies can communicatedirectly with the W4 COMN or can communicate with the W4 COMN using IOssuch as applications executed on or by a proxy device.

In one embodiment, the proxy devices 104, 106, 108, 110 can beexplicitly associated with the user 102. For example, one device 104 canbe a smart phone connected by a cellular service provider to the networkand another device 106 can be a smart vehicle that is connected to thenetwork. Other devices can be implicitly associated with the user 102.

For example, one device 108 can be a “dumb” weather sensor at a locationmatching the current location of the user's cell phone 104, and thusimplicitly associated with the user 102 while the two RWEs 104, 108 areco-located. Another implicitly associated device 110 can be a sensor 110for physical location 112 known to the W4 COMN. The location 112 isknown, either explicitly (through a user-designated relationship, e.g.,this is my home, place of employment, parent, etc.) or implicitly (theuser 102 is often co-located with the RWE 112 as evidenced by data fromthe sensor 110 at that location 112), to be associated with the firstuser 102.

The user 102 can be directly associated with one or more persons 140,and indirectly associated with still more persons 142, 144 through achain of direct associations. Such associations can be explicit (e.g.,the user 102 can have identified the associated person 140 as his/herfather, or can have identified the person 140 as a member of the user'ssocial network) or implicit (e.g., they share the same address).Tracking the associations between people (and other RWEs as well) allowsthe creation of the concept of “intimacy”, where intimacy may be definedas a measure of the degree of association between two people or RWEs.For example, each degree of removal between RWEs can be considered alower level of intimacy, and assigned lower intimacy score. Intimacy canbe based solely on explicit social data or can be expanded to includeall W4 data including spatial data and temporal data.

In one embodiment, each RWE 102, 104, 106, 108, 110, 112, 140, 142, 144of a W4 COMN can be associated with one or more IOs as shown. FIG. 1illustrates two IOs 122, 124 as associated with the cell phone device104. One IO 122 can be a passive data object such as an event recordthat is used by scheduling/calendaring software on the cell phone, acontact IO used by an address book application, a historical record of atransaction made using the device 104 or a copy of a message sent fromthe device 104. The other IO 124 can be an active software process orapplication that serves as the device's proxy to the W4 COMN bytransmitting or receiving data via the W4 COMN. Voice communicationsoftware, scheduling/calendaring software, an address book applicationor a text messaging application are all examples of IOs that cancommunicate with other IOs and RWEs on the network. IOs may additionallyrelate to topics of interest to one or more RWEs, such topics including,without limitation, musical artists, genre of music, a location and soforth.

The IOs 122, 124 can be locally stored on the device 104 or storedremotely on some node or datastore accessible to the W4 COMN, such as amessage server or cell phone service datacenter. The IO 126 associatedwith the vehicle 108 can be an electronic file containing thespecifications and/or current status of the vehicle 108, such as make,model, identification number, current location, current speed, currentcondition, current owner, etc. The IO 128 associated with sensor 108 canidentify the current state of the subject(s) monitored by the sensor108, such as current weather or current traffic. The IO 130 associatedwith the cell phone 110 can be information in a database identifyingrecent calls or the amount of charges on the current bill.

RWEs which can only interact with the W4 COMN through proxies, such aspeople 102, 140, 142, 144, computing devices 104, 106 and locations 112,can have one or more IOs 132, 134, 146, 148, 150 directly associatedwith them which contain RWE-specific information for the associated RWE.For example, IOs associated with a person 132, 146, 148, 150 can includea user profile containing email addresses, telephone numbers, physicaladdresses, user preferences, identification of devices and other RWEsassociated with the user. The IOs may additionally include records ofthe user's past interactions with other RWE's on the W4 COMN (e.g.,transaction records, copies of messages, listings of time and locationcombinations recording the user's whereabouts in the past), the uniqueW4 COMN identifier for the location and/or any relationship information(e.g., explicit user-designations of the user's relationships withrelatives, employers, co-workers, neighbors, service providers, etc.).

Another example of IOs associated with a person 132, 146, 148, 150includes remote applications through which a person can communicate withthe W4 COMN such as an account with a web-based email service such asYahoo! Mail. A location's IO 134 can contain information such as theexact coordinates of the location, driving directions to the location, aclassification of the location (residence, place of business, public,non-public, etc.), information about the services or products that canbe obtained at the location, the unique W4 COMN identifier for thelocation, businesses located at the location, photographs of thelocation, etc.

In one embodiment, RWEs and IOs are correlated to identify relationshipsbetween them. RWEs and IOs may be correlated using metadata. Forexample, if an IO is a music file, metadata for the file can includedata identifying the artist, song, etc., album art, and the format ofthe music data. This metadata can be stored as part of the music file orin one or more different IOs that are associated with the music file orboth. W4 metadata can additionally include the owner of the music fileand the rights the owner has in the music file. As another example, ifthe IO is a picture taken by an electronic camera, the picture caninclude in addition to the primary image data from which an image can becreated on a display, metadata identifying when the picture was taken,where the camera was when the picture was taken, what camera took thepicture, who, if anyone, is associated (e.g., designated as the camera'sowner) with the camera, and who and what are the subjects of/in thepicture. The W4 COMN uses all the available metadata in order toidentify implicit and explicit associations between entities and dataobjects.

FIG. 2 illustrates one embodiment of metadata defining the relationshipsbetween RWEs and IOs on the W4 COMN. In the embodiment shown, an IO 202includes object data 204 and five discrete items of metadata 206, 208,210, 212, 214. Some items of metadata 208, 210, 212 can containinformation related only to the object data 204 and unrelated to anyother IO or RWE. For example, a creation date, text or an image that isto be associated with the object data 204 of the IO 202.

Some of items of metadata 206, 214, on the other hand, can identifyrelationships between the IO 202 and other RWEs and IOs. As illustrated,the IO 202 is associated by one item of metadata 206 with an RWE 220that RWE 220 is further associated with two IOs 224, 226 and a secondRWE 222 based on some information known to the W4 COMN. For example,could describe the relations between an image (IO 202) containingmetadata 206 that identifies the electronic camera (the first RWE 220)and the user (the second RWE 224) that is known by the system to be theowner of the camera 220. Such ownership information can be determined,for example, from one or another of the IOs 224, 226 associated with thecamera 220.

FIG. 2 also illustrates metadata 214 that associates the IO 202 withanother IO 230. This IO 230 is itself associated with three other IOs232, 234, 236 that are further associated with different RWEs 242, 244,246. This part of FIG. 2, for example, could describe the relationsbetween a music file (IO 202) containing metadata 206 that identifiesthe digital rights file (the first IO 230) that defines the scope of therights of use associated with this music file 202. The other IOs 232,234, 236 are other music files that are associated with the rights ofuse and which are currently associated with specific owners (RWEs 242,244, 246).

FIG. 3 illustrates one embodiment of a conceptual model of a W4 COMN.The W4 COMN 300 creates an instrumented messaging infrastructure in theform of a global logical network cloud conceptually sub-divided intonetworked-clouds for each of the 4Ws: Who, Where, What and When. In theWho cloud 302 are all users whether acting as senders, receivers, datapoints or confirmation/certification sources as well as user proxies inthe forms of user-program processes, devices, agents, calendars, etc.

In the Where cloud 304 are all physical locations, events, sensors orother RWEs associated with a spatial reference point or location. TheWhen cloud 306 is composed of natural temporal events (that is eventsthat are not associated with particular location or person such as days,times, seasons) as well as collective user temporal events (holidays,anniversaries, elections, etc.) and user-defined temporal events(birthdays, smart-timing programs).

The What cloud 308 is comprised of all known data—web or private,commercial or user—accessible to the W4 COMN, including for exampleenvironmental data like weather and news, RWE-generated data, IOs and IOdata, user data, models, processes and applications. Thus, conceptually,most data is contained in the What cloud 308.

Some entities, sensors or data may potentially exist in multiple cloudseither disparate in time or simultaneously. Additionally, some IOs andRWEs can be composites in that they combine elements from one or moreclouds. Such composites can be classified as appropriate to facilitatethe determination of associations between RWEs and IOs. For example, anevent consisting of a location and time could be equally classifiedwithin the When cloud 306, the What cloud 308 and/or the Where cloud304.

In one embodiment, a W4 engine 310 is center of the W4 COMN'sintelligence for making all decisions in the W4 COMN. The W4 engine 310controls all interactions between each layer of the W4 COMN and isresponsible for executing any approved user or application objectiveenabled by W4 COMN operations or interoperating applications. In anembodiment, the W4 COMN is an open platform with standardized, publishedAPIs for requesting (among other things) synchronization,disambiguation, user or topic addressing, access rights, prioritizationor other value-based ranking, smart scheduling, automation and topical,social, spatial or temporal alerts.

One function of the W4 COMN is to collect data concerning allcommunications and interactions conducted via the W4 COMN, which caninclude storing copies of IOs and information identifying all RWEs andother information related to the IOs (e.g., who, what, when, whereinformation). Other data collected by the W4 COMN can includeinformation about the status of any given RWE and IO at any given time,such as the location, operational state, monitored conditions (e.g., foran RWE that is a weather sensor, the current weather conditions beingmonitored or for an RWE that is a cell phone, its current location basedon the cellular towers it is in contact with) and current status.

The W4 engine 310 is also responsible for identifying RWEs andrelationships between RWEs and IOs from the data and communicationstreams passing through the W4 COMN. The function of identifying RWEsassociated with or implicated by IOs and actions performed by other RWEsmay be referred to as entity extraction. Entity extraction can includeboth simple actions, such as identifying the sender and receivers of aparticular IO, and more complicated analyses of the data collected byand/or available to the W4 COMN, for example determining that a messagelisted the time and location of an upcoming event and associating thatevent with the sender and receiver(s) of the message based on thecontext of the message or determining that an RWE is stuck in a trafficjam based on a correlation of the RWE's location with the status of aco-located traffic monitor.

It should be noted that when performing entity extraction from an IO,the IO can be an opaque object with only where only W4 metadata relatedto the object is visible, but internal data of the IO (i.e., the actualprimary or object data contained within the object) are not, and thusmetadata extraction is limited to the metadata. Alternatively, ifinternal data of the IO is visible, it can also be used in entityextraction, e.g. strings within an email are extracted and associated asRWEs to for use in determining the relationships between the sender,user, topic or other RWE or IO impacted by the object or process.

In the embodiment shown, the W4 engine 310 can be one or a group ofdistributed computing devices, such as a genrel-purpose personalcomputers (PCs) or purpose built server computers, connected to the W4COMN by communication hardware and/or software. Such computing devicescan be a single device or a group of devices acting together. Computingdevices can be provided with any number of program modules and datafiles stored in a local or remote mass storage device and local memory(e.g., RAM) of the computing device. For example, as mentioned above, acomputing device can include an operating system suitable forcontrolling the operation of a networked computer, such as the WINDOWSXP or WINDOWS SERVER operating systems from MICROSOFT CORPORATION.

Some RWEs can also be computing devices such as, without limitation,smart phones, web-enabled appliances, PCs, laptop computers, andpersonal data assistants (PDAs). Computing devices can be connected toone or more communications networks such as the Internet, a publiclyswitched telephone network, a cellular telephone network, a satellitecommunication network, a wired communication network such as a cabletelevision or private area network. Computing devices can be connectedany such network via a wired data connection or wireless connection suchas a wi-fi, a WiMAX (802.36), a Bluetooth or a cellular telephoneconnection.

Local data structures, including discrete IOs, can be stored on acomputer-readable medium (not shown) that is connected to, or part ofany of the computing devices described herein including the W4 engine310. For example, in one embodiment, the data backbone of the W4 COMN,discussed below, includes multiple mass storage devices that maintainthe IOs, metadata and data necessary to determine relationships betweenRWEs and IOs as described herein.

FIG. 4 illustrates one embodiment of the functional layers of a W4 COMNarchitecture. At the lowest layer, referred to as the sensor layer 402,is the network 404 of the actual devices, users, nodes and other RWEs.Sensors include known technologies like web analytics, GPS, cell-towerpings, use logs, credit card transactions, online purchases, explicituser profiles and implicit user profiling achieved through behavioraltargeting, search analysis and other analytics models used to optimizespecific network applications or functions.

The data layer 406 stores and catalogs the data produced by the sensorlayer 402. The data can be managed by either the network 404 of sensorsor the network infrastructure 406 that is built on top of theinstrumented network of users, devices, agents, locations, processes andsensors. The network infrastructure 408 is the core under-the-coversnetwork infrastructure that includes the hardware and software necessaryto receive that transmit data from the sensors, devices, etc. of thenetwork 404. It further includes the processing and storage capabilitynecessary to meaningfully categorize and track the data created by thenetwork 404.

The user profiling layer 410 performs the W4 COMN's user profilingfunctions. This layer 410 can further be distributed between the networkinfrastructure 408 and user applications/processes 412 executing on theW4 engine or disparate user computing devices. Personalization isenabled across any single or combination of communication channels andmodes including email, IM, texting (SMS, etc.), photobloging, audio(e.g. telephone call), video (teleconferencing, live broadcast), games,data confidence processes, security, certification or any other W4 COMMprocess call for available data.

In one embodiment, the user profiling layer 410 is a logic-based layerabove all sensors to which sensor data are sent in the rawest form to bemapped and placed into the W4 COMN data backbone 420. The data(collected and refined, related and deduplicated, synchronized anddisambiguated) are then stored in one or a collection of relateddatabases available applications approved on the W4 COMN.Network-originating actions and communications are based upon the fieldsof the data backbone, and some of these actions are such that theythemselves become records somewhere in the backbone, e.g. invoicing,while others, e.g. fraud detection, synchronization, disambiguation, canbe done without an impact to profiles and models within the backbone.

Actions originating from outside the network, e.g., RWEs such as users,locations, proxies and processes, come from the applications layer 414of the W4 COMN. Some applications can be developed by the W4 COMNoperator and appear to be implemented as part of the communicationsinfrastructure 408, e.g. email or calendar programs because of howclosely they operate with the sensor processing and user profiling layer410. The applications 412 also serve as a sensor in that they, throughtheir actions, generate data back to the data layer 406 via the databackbone concerning any data created or available due to theapplications execution.

In one embodiment, the applications layer 414 can also provide a userinterface (UI) based on device, network, carrier as well asuser-selected or security-based customizations. Any UI can operatewithin the W4 COMN if it is instrumented to provide data on userinteractions or actions back to the network. In the case of W4 COMNenabled mobile devices, the UI can also be used to confirm ordisambiguate incomplete W4 data in real-time, as well as correlation,triangulation and synchronization sensors for other nearby enabled ornon-enabled devices.

At some point, the network effects enough enabled devices allow thenetwork to gather complete or nearly complete data (sufficient forprofiling and tracking) of a non-enabled device because of its regularintersection and sensing by enabled devices in its real-world location.

Above the applications layer 414, or hosted within it, is thecommunications delivery network 416. The communications delivery networkcan be operated by the W4 COMN operator or be independent third-partycarrier service. Data may be delivered via synchronous or asynchronouscommunication. In every case, the communication delivery network 414will be sending or receiving data on behalf of a specific application ornetwork infrastructure 408 request.

The communication delivery layer 418 also has elements that act assensors including W4 entity extraction from phone calls, emails, blogs,etc. as well as specific user commands within the delivery networkcontext. For example, “save and prioritize this call” said before end ofcall can trigger a recording of the previous conversation to be savedand for the W4 entities within the conversation to analyzed andincreased in weighting prioritization decisions in thepersonalization/user profiling layer 410.

FIG. 5 illustrates one embodiment of the analysis components of a W4engine as shown in FIG. 3. As discussed above, the W4 Engine isresponsible for identifying RWEs and relationships between RWEs and IOsfrom the data and communication streams passing through the W4 COMN.

In one embodiment the W4 engine connects, interoperates and instrumentsall network participants through a series of sub-engines that performdifferent operations in the entity extraction process. The attributionengine 504 tracks the real-world ownership, control, publishing or otherconditional rights of any RWE in any IO. Whenever a new IO is detectedby the W4 engine 502, e.g., through creation or transmission of a newmessage, a new transaction record, a new image file, etc., ownership isassigned to the IO. The attribution engine 504 creates this ownershipinformation and further allows this information to be determined foreach IO known to the W4 COMN.

The correlation engine 506 can operates two capacities: first, toidentify associated RWEs and IOs and their relationships (such as bycreating a combined graph of any combination of RWEs and IOs and theirattributes, relationships and reputations within contexts or situations)and second, as a sensor analytics pre-processor for attention eventsfrom any internal or external source.

In one embodiment, the identification of associated RWEs and IOsfunction of the correlation engine 506 is done by graphing the availabledata, using, for example, one or more histograms A histogram is amapping technique that counts the number of observations that fall intovarious disjoint categories (i.e. bins.). By selecting each IO, RWE, andother known parameters (e.g., times, dates, locations, etc.) asdifferent bins and mapping the available data, relationships betweenRWEs, IOs and the other parameters can be identified. A histogram of allRWEs and IOs is created, from which correlations based on the graph canbe made.

As a pre-processor, the correlation engine 506 monitors the informationprovided by RWEs in order to determine if any conditions are identifiedthat can trigger an action on the part of the W4 engine 502. Forexample, if a delivery condition has been associated with a message,when the correlation engine 506 determines that the condition is met, itcan transmit the appropriate trigger information to the W4 engine 502that triggers delivery of the message.

The attention engine 508 instruments all appropriate network nodes,clouds, users, applications or any combination thereof and includesclose interaction with both the correlation engine 506 and theattribution engine 504.

FIG. 6 illustrates one embodiment of a W4 engine showing differentcomponents within the sub-engines described above with reference to FIG.4. In one embodiment the W4 engine 602 includes an attention engine 608,attribution engine 604 and correlation engine 606 with severalsub-managers based upon basic function.

The attention engine 608 includes a message intake and generationmanager 610 as well as a message delivery manager 612 that work closelywith both a message matching manager 614 and a real-time communicationsmanager 616 to deliver and instrument all communications across the W4COMN.

The attribution engine 604 works within the user profile manager 618 andin conjunction with all other modules to identify, process/verify andrepresent ownership and rights information related to RWEs, IOs andcombinations thereof.

The correlation engine 606 dumps data from both of its channels (sensorsand processes) into the same data backbone 620 which is organized andcontrolled by the W4 analytics manager 622. The data backbone 620includes both aggregated and individualized archived versions of datafrom all network operations including user logs 624, attention rankplace logs 626, web indices and environmental logs 618, e-commerce andfinancial transaction information 630, search indexes and logs 632,sponsor content or conditionals, ad copy and any and all other data usedin any W4COMN process, IO or event. Because of the amount of data thatthe W4 COMN will potentially store, the data backbone 620 includesnumerous database servers and datastores in communication with the W4COMN to provide sufficient storage capacity.

The data collected by the W4 COMN includes spatial data, temporal data,RWE interaction data, IO content data (e.g., media data), and user dataincluding explicitly-provided and deduced social and relationship data.Spatial data can be any data identifying a location associated with anRWE. For example, the spatial data can include any passively collectedlocation data, such as cell tower data, global packet radio service(GPRS) data, global positioning service (GPS) data, WI-FI data, personalarea network data, IP address data and data from other network accesspoints, or actively collected location data, such as location dataentered by the user.

Temporal data is time based data (e.g., time stamps) that relate tospecific times and/or events associated with a user and/or theelectronic device. For example, the temporal data can be passivelycollected time data (e.g., time data from a clock resident on theelectronic device, or time data from a network clock), or the temporaldata can be actively collected time data, such as time data entered bythe user of the electronic device (e.g., a user maintained calendar).

Logical and IO data refers to the data contained by an IO as well asdata associated with the IO such as creation time, owner, associatedRWEs, when the IO was last accessed, the topic or subject of the IO(from message content or “re” or subject line, as some examples) etc.For example, an IO may relate to media data. Media data can include anydata relating to presentable media, such as audio data, visual data, andaudiovisual data. Audio data can be data relating to downloaded music,such as genre, artist, album and the like, and includes data regardingringtones, ringbacks, media purchased, playlists, and media shared, toname a few. The visual data can be data relating to images and/or textreceived by the electronic device (e.g., via the Internet or othernetwork). The visual data can be data relating to images and/or textsent from and/or captured at the electronic device.

Audiovisual data can be data associated with any videos captured at,downloaded to, or otherwise associated with the electronic device. Themedia data includes media presented to the user via a network, such asuse of the Internet, and includes data relating to text entered and/orreceived by the user using the network (e.g., search terms), andinteraction with the network media, such as click data (e.g.,advertisement banner clicks, bookmarks, click patterns and the like).Thus, the media data can include data relating to the user's RSS feeds,subscriptions, group memberships, game services, alerts, and the like.

The media data can include non-network activity, such as image captureand/or video capture using an electronic device, such as a mobile phone.The image data can include metadata added by the user, or other dataassociated with the image, such as, with respect to photos, locationwhen the photos were taken, direction of the shot, content of the shot,and time of day, to name a few. Media data can be used, for example, todeduce activities information or preferences information, such ascultural and/or buying preferences information.

Relationship data can include data relating to the relationships of anRWE or IO to another RWE or IO. For example, the relationship data caninclude user identity data, such as gender, age, race, name, socialsecurity number, photographs and other information associated with theuser's identity. User identity information can also include e-mailaddresses, login names and passwords. Relationship data can furtherinclude data identifying explicitly associated RWEs. For example,relationship data for a cell phone can indicate the user that owns thecell phone and the company that provides the service to the phone. Asanother example, relationship data for a smart car can identify theowner, a credit card associated with the owner for payment of electronictolls, those users permitted to drive the car and the service stationfor the car.

Relationship data can also include social network data. Social networkdata includes data relating to any relationship that is explicitlydefined by a user or other RWE, such as data relating to a user'sfriends, family, co-workers, business relations, and the like. Socialnetwork data can include, for example, data corresponding with auser-maintained electronic address book. Relationship data can becorrelated with, for example, location data to deduce social networkinformation, such as primary relationships (e.g., user-spouse,user-children and user-parent relationships) or other relationships(e.g., user-friends, user-co-worker, user-business associaterelationships). Relationship data also can be utilized to deduce, forexample, activities information.

Interaction data can be any data associated with user interaction of theelectronic device, whether active or passive. Examples of interactiondata include interpersonal communication data, media data, relationshipdata, transactional data and device interaction data, all of which aredescribed in further detail below. Table 1, below, is a non-exhaustivelist including examples of electronic data.

TABLE 1 Examples of Electronic Data Spatial Data Temporal DataInteraction Data Cell tower Time stamps Interpersonal GPRS Local clockcommunications GPS Network clock Media WiFi User input of timeRelationships Personal area network Transactions Network access pointsDevice interactions User input of location Geo-coordinates

Interaction data includes communication data between any RWEs that istransferred via the W4 COMN. For example, the communication data can bedata associated with an incoming or outgoing short message service (SMS)message, email message, voice call (e.g., a cell phone call, a voiceover IP call), or other type of interpersonal communication related toan RWE. Communication data can be correlated with, for example, temporaldata to deduce information regarding frequency of communications,including concentrated communication patterns, which can indicate useractivity information.

The interaction data can also include transactional data. Thetransactional data can be any data associated with commercialtransactions undertaken by or at the mobile electronic device, such asvendor information, financial institution information (e.g., bankinformation), financial account information (e.g., credit cardinformation), merchandise information and costs/prices information, andpurchase frequency information, to name a few. The transactional datacan be utilized, for example, to deduce activities and preferencesinformation. The transactional information can also be used to deducetypes of devices and/or services the user owns and/or in which the usercan have an interest.

The interaction data can also include device or other RWE interactiondata. Such data includes both data generated by interactions between auser and a RWE on the W4 COMN and interactions between the RWE and theW4 COMN. RWE interaction data can be any data relating to an RWE'sinteraction with the electronic device not included in any of the abovecategories, such as habitual patterns associated with use of anelectronic device data of other modules/applications, such as dataregarding which applications are used on an electronic device and howoften and when those applications are used. As described in furtherdetail below, device interaction data can be correlated with other datato deduce information regarding user activities and patterns associatedtherewith. Table 2, below, is a non-exhaustive list including examplesof interaction data.

TABLE 2 Examples of Interaction Data Type of Data Example(s)Interpersonal Text-based communications, such as SMS and e-communication data mail Audio-based communications, such as voice calls,voice notes, voice mail Media-based communications, such as multimediamessaging service (MMS) communications Unique identifiers associatedwith a communication, such as phone numbers, e-mail addresses, andnetwork addresses Media data Audio data, such as music data (artist,genre, track, album, etc.) Visual data, such as any text, images andvideo data, including Internet data, picture data, podcast data andplaylist data Network interaction data, such as click patterns andchannel viewing patterns Relationship data User identifying information,such as name, age, gender, race, and social security number Socialnetwork data Transactional data Vendors Financial accounts, such ascredit cards and banks data Type of merchandise/services purchased Costof purchases Inventory of purchases Device interaction data Any data notcaptured above dealing with user interaction of the device, such aspatterns of use of the device, applications utilized, and so forth

Presentation of Media Related to a Context

Media such as music, videos, movies, images, books and publications helpdefine and shape human consciousness. Media may evoke deep seatedmemories and create a picture, an impression, a feeling, of a time orplace, a person or a group of persons, or even an abstract idea. Solittle is within the compass of direct experience, yet through the lensof recorded media, a person can glimpse a flash of another place ortime, may in fact, be able to enter the thoughts of another person. Thepast and the present, and the far reaches of the world carry on anunbroken dialogue through media.

A person may wish, for any number of reasons, to set sail on the oceanof available media to capture an idea, a place, a time, and to live it,think it, experience it on a conscious or unconscious level. It issimple enough to retrieve a playlist or list of videos for a singlemusical artist. But a person may wish to capture a more complex concept,for example, a person may wish to create a playlist of songsrepresenting the favorite music of immediate family members when each ofthe family members were a particular age. In another example, a personmay wish to listen to music listened to by surfers in Hawaii in 1974.

More abstractly, when a user is requesting a playlist, the user may besaid to have a specific context in mind. In one embodiment, the user'scontext can be defined as a set of criteria that describe orcircumscribe one or more related ideas. The criteria can be conceptuallydivided into four categories: Who, What, When and Where.

“Who” criteria are persons, devices, or proxies who are related to theideas embodied in the context. “Who” may be a known person, such as theuser or a specific person known by the user. “Who” may also be a list ofspecific persons, such as the contact list stored on the PDA of a user,or persons listed on a user's social network profile as friends.Alternatively, “Who” can be a genrel description of persons of interest,such as persons who are interested in surfing.

“What” criteria are objects or topics related to the ideas embodied inthe context. “What” may be the form of media the user is interested in,such as music or videos. “What” may be a genre of music or video, suchas country or rock. “What” may be subject matter addressed in media,such as love songs or even specific lyrical phrases. Alternatively,“What” may be a mood or atmosphere, such as happy, sad, energetic, orrelaxed.

“When” criteria are dates and times which are related to the ideasembodied in the context. “When” may be the current date and time. “When”may also be a specific date and time in the past or the future, or arange of dates and times in the past or the future. “When” may be anoffset from a specific date, for example, ten days in the past.Alternatively, “When” can be an event on a calendar, such as a birthday,a season or a holiday, or an event in the news, such as the last time afavorite sports team won a championship.

“Where” criteria are physical locations. “Where” may be a user's currentlocation. “Where” may be specific place, such as a country, a state, acity, a neighborhood. “Where” may be defined as the location of anevent, such as a concert or some other newsworthy occurrence.Alternatively, “Where” can be a general description of places ofinterest, such as blues or jazz clubs.

The embodiments of the present invention discussed below illustrateapplication of the present invention within a W4 COMN. Nevertheless, itis understood that the invention can be implemented using any networkedsystem that is capable of collecting, storing accessing and/orprocessing user profile data, as well as temporal, spatial, topical andsocial data relating to users and their devices. Thus the term W4 COMNis used herein for convenience to describe a system and/or networkhaving the features, functions and/or components described hereinthroughout.

A W4 COMN can provide a platform that stores media files and enables theselection and presentation of such files related using queries based oncomplex contexts containing who, what, when, and where criteria,allowing a user to experience or re-experience the media of a specificcombination of time, place and social network by mining historical andcurrent W4 data, and combining it with, among other things, charts ofpopular media at the specific time and place specified.

FIG. 7 illustrates one embodiment of a data model showing how a W4 COMNcan store media files and relate such files to RWEs, such as persons andplaces, and IOs, such as topics and other types of metadata.

In the illustrated embodiment, media is stored as media objects 710.Media objects are passive IOs relating to media files containing audiocontent, visual content, or both. Such media files can contain contentsuch as songs, videos, pictures, images, audio messages, phone calls,and so forth. The media objects themselves contain metadata 712. Suchdata may be specific to the to the object data 710 and unrelated to anyother IO or RWE. At the simplest level, such metadata may relate tobasic file properties such as creation date, text or an image that isassociated with a media file to which an IO relates.

Additionally, there are existing databases 720 which can reside withinor outside of the network that can provide an extensive set ofdescriptive metadata relating to specific songs, videos and other typesof media. For example, the Allmusic database (formerly the All MusicGuide, owned by All Media Guide) provides metadata which includes:

-   -   Basic metadata such as names, genres, credits, copyright        information, product numbers.    -   Descriptive content such as styles, tones, moods, themes,        nationalities, etc.    -   Relational content such as similar artists and albums,        influences, etc.    -   Editorial content such as biographies, reviews, rankings, etc.

Other types of databases that can be used as sources for metadatarelating to songs and video include:

-   -   Historical billboard rankings at a local, regional, or national        level, or on foreign billboards.    -   Music and video industry news.    -   Music lyrics.

In one embodiment, metadata originating from such databases canextracted from source databases and embedded 712 in the media objects710 themselves. Alternatively or additionally, the media objects may berelated to IOs that contain or relate to metadata 740. Metadata caninclude one or more keywords or topics that describe or classify data.For example, a IO relating to metadata can be an topics that relates toall songs within a genre, such as rock, or all songs performed at aspecific festival, such as Woodstock. Topic or IOs relating to metadatacan be associated with IOs relating to higher level topics 742. Forexample, a composer may be associated with a topic such as baroquemusic, which is itself associated with a higher-level IO for classicalmusic.

Alternatively or additionally, a metadata server with its associateddatabases can be defined as an RWE 722 within the W4 COMN, and mediaobjects and other IOs can be associated with the RWE 722. In oneembodiment, metadata relating to a media object can then be retrieved ondemand, rather than being stored in static metadata or in a persistentIO. Metadata retrieved on demand can be chosen based on needs of userswho have a potential interest in the media object. For example, a userwho initially selects a media object based on a topic can then retrievemetadata on demand relating to tone or mood of the music associated withthe media object.

If a user wishes to select media objects using a topic for which notopics exists, for example, the top 10 hits in the U.K. in 1975, ametadata server which is capable of providing such information can bequeried to retrieve a list of such songs. In one embodiment, the list ofsongs can be used to create an IO relating to a topic, such as IO 740,by associating media objects relating to the list of songs with a newlycreated IO. In one embodiment, such an IO is created by a correlationengine within a W4 engine (see above and FIGS. 4 through 6, forexample). The IO can then be used in subsequent queries.

In one embodiment, media objects are associated with other RWEs, such asmusical rights holders 730 (i.e. owners and licensees), and interestedlisteners 750. In one embodiment, where an owner 730 of a media objectcan be identified, an attribution engine within a W4 engine tracks thereal-world ownership, control, publishing or other conditional rights ofany RWE in any media IO whenever a new object is detected.

In one embodiment, users 750, 752, and 754 can be identified as havingan interest in a specific song 710 or a topic IO 740 or 742 by acorrelation engine within a W4 engine. In one embodiment, thecorrelation engine identifies relationships between user RWEs and mediaor IOs relating to metadata by creating a combined graph of the RWEs andIOs and their attributes, relationships and reputations. For example, auser can explicitly state in a user profile that they have an interestin a specific musical artist. Alternatively, the correlation engine candetermine a user's interest in a topic or a song or view based on thecontent of the user's interaction data, sensing attention events fromany internal or external source.

In one embodiment, the W4 COMN builds a profile of a user over time bycollecting data from the user or from information sources available tothe network so as to gain an understanding of where they were born,where they have lived, and where they live today. Using social data, theW4 COMN can also create an overlapping social network profile whichplaces the user in a temporal, geographic and social graph, thusdetermining where a user lived when and with whom. User RWEs can be alsobe associated with other RWEs through interaction data. Users who areinterested in the same time/place can declare their interests and beconnected to a topic based social network through, for example, an IOrelating to a topic. In the illustrated embodiment in FIG. 7, users 750and 752 are identified as being within a social network, 760.

Thus, media objects can be stored and associated with temporal, spatial,social network and topical data derived from, without limitation,traditional metadata sources, user profile data, social networks, andinteraction data, building a network of relationships across theuniverse of media and users. Such relationships may be built on demand,if necessary. Such relationships can then enable queries for media thatsatisfy the criteria of simple or complex contexts.

FIG. 8 illustrates one embodiment of a process 800 of how a networkcontaining temporal, spatial, and social network and topical data for aplurality of users, devices, and media (such as a W4 COMN), can be usedto enable customized music delivery for complex user contexts havingwho, where, when, and what criteria.

The process begins when a user enters a context criteria 820 using auser proxy device such as, for example, a portable media player, PDA,computer, or cell phone. Data relating to the context can be anycombination be any who, what, when, or where criteria. In oneembodiment, the criteria can be related to one another using standardrelational or set operators. In one embodiment, the query can be statedas a natural language query

The context is used to formulate a query based on the context criteriaso as to search, via the network, for user profile data, social networkdata, spatial data, temporal data and topical data that is available viathe network 842 and relates to the context and to media files so as toidentify at least one media file that is relevant to the contextcriteria.

In one embodiment, the criteria are interpreted to take advantage thebest available data within the network. A context may be defined ingeneral terms, but the proper data and access paths may not be apparentto an end user. For example, assume a user enters a query “Play thefavorite music of surfers in Hawaii in 1974.”

One interpretation of such a query would be to retrieve songs in thegenre “surf music”, released in 1974 whose lyrics reference Hawaii. Suchan interpretation may be appropriate if the network has data limited tomusic metadata, but does not fully address the query—surfers in Hawaii1974 might have liked blues or jazz. The requesting user may, be unawareof, or may not fully appreciate that, the network stores data for alarge number of other users. A subset of such users may be users whosehobby is surfing and who lived in Hawaii in 1974.

The query could search for users known to the network whose profile orinteraction data indicate have surfing as a hobby or interest and wholived in Hawaii in 1974. The musical preferences of such users, such asmusical genre, favorite artists, or favorite songs could then be used tosearch for media objects for songs relating to such genre, artists, orsongs and which were released in 1974.

The query results are then used to assemble a playlist 860 that, incertain embodiments, can be stored on a computer readable medium 862referencing one or more media objects or files relevant to the context.The playlist 862 is then used to download, stream, or otherwise delivermedia 880 on the playlist to one or more user devices associated withthe requesting user In one embodiment, a query may be recursivelyexecuted 890 and the results delivered based on a trigger condition, forexample, if the physical location of the end user changes or if the userarrives at a predetermined location, or at a specific time of day or dayof the week.

FIG. 9 further illustrates how the process illustrated in FIG. 8 can besupported by one embodiment of a W4 COMN or other network providingsimilar data and processing capabilities.

A context query engine 912 resides on a server 910 within the W4 COMN.The context query engine 912 can be defined to the W4 COMN as an RWE, oralternatively, an active IO. The context query engine can be a componentof a W4 engine, or, alternatively, may use services provided bycomponents of a W4 engine or any of its constituent engines.

The context query engine 912 provides a user interface on a user'sportable media player 924 (known to the network as a user proxy RWE 926)or other media capable device or application, that enables a user 920(known to the network as an RWE 922) to enter a context. The end userdevice 924 may contain positioning or other sensors that detect variousaspects of the physical environment surrounding the user 920, such as,for example, the user's geographical location. Sensors can also includeother environmental sensors such as temperature and lighting sensors, orcan also include biometric sensors. Sensed data can be included in thecontext automatically, or some or all can be included by explicit userselection or by system selection.

The context query engine 912 can use the context data entered on themedia player 924 to create an IO 930 relating to the context data ownedby the proxy RWE 926 associated with the media player 924. The IO 930may alternatively or additionally be owned by the user RWE 922. The IO930 is input to the context query engine 912 which searches the W4 COMNdatabases and assembles a playlist IO 940 which references media objects950, 952, 954, and 956 which the context query engine has identified asrelevant to the query IO 930.

The context query engine 912 can identify media objects of interestusing relationships existing in the W4 COMN databases. Examples include:media 950 directly related to the user RWE 922 (e.g. a user's favoritesong); media 952 related to a IO relating to a topic 945; media 945related to another user 955; and media 956 identified based on metadataembedded within the media object. In one embodiment, such relationshipsbetween entities and data objects are stored in a global index withinthe W4 COMN databases and the context query engine 912 uses the globalindex to identify media objects of interest.

The user's 920 media player 922, or a software application provided bythe media player can use the playlist 930 to request delivery of themedia in the playlist to the media player from, for example, a mediaserver or media provider or streaming media server (not shown).Alternatively, the query engine can send the playlist directly to amedia server or media provider or streaming media server for delivery ofthe media to the user's 920 media player 922.

FIG. 10 illustrates the components of one embodiment of a context queryengine 1000. In one embodiment, the context query engine is a componentof a W4 engine 502 within a W4 COMN, such as the context query engine912 shown in FIG. 9. In alternative embodiments, the context queryengine 1000 is a standalone application that has access to one or moredatabases containing temporal, spatial, social network and topical datarelating to one or more users.

The context query engine 1000 includes: a context entry module 1200 thatprovides a user interface for entry of criteria for contexts; a querymodule 1300 that searches network databases 1320 for media related tocontext criteria; a playlist generation module 1400 that generatesplaylists 1420 using the search results produced by the query module1300; and a media delivery module 1500 that delivers the mediareferenced in the playlist to a device associated with the requestinguser. Any of the aforementioned modules or the communications betweenmodules (e.g. the playlist or the query) may be stored on computerreadable media, for transient, temporary or permanent stage.

The interface provided by the context a context entry module 1200 may bea graphical user interface displayable on computers or PDAs, includingHTTP documents accessible over the Internet. Such an interfaces may alsotake other forms, including text files, such as emails, and APIs usableby software applications located on computing devices.

In one embodiment, the criteria can be related to one another usingstandard relational or set operators. In one embodiment, temporal andspatial data obtained from sensors within user devices can be includedin the context criteria. For example, the current location of a deviceassociated with a user can be automatically identified and included inthe context. The user creating the context can be automaticallyidentified through the association of the proxy device with a userwithin the network and automatically included in the context.

In one embodiment, the context can further specify that the context beprocessed at a future point in time, periodically, or on the occurrenceof a specific event. For example, a context may specify that the contextbe reprocessed on the occurrence of a trigger condition, such as hourly,when the physical location of a user associated with the contextchanges, when a calendared event occurs (e.g. an anniversary), or when anews event occurs (e.g. a favorite sports team wins a game.)

In one embodiment, a context can be associated with an advertisement.When a user views an advertisement, a context is entered and processedto generate a playlist which relates to the context, such as a specificera or other topic, and which may further take into account the user'stemporal, spatial, social, and topical associations. Thus, anadvertisement may supplement basic ad content with media tailored for aspecific user. For example, an advertisement for a sports car may beassociated with a context specifying the users favorite musical artistand songs with a fast tempo or explicit references to speed, or the year1975 when the user last owned a sports car.

The query module 1300 searches one or more network databases 1320, foruser profile data, social network data, spatial data, temporal data andtopical data that is available via the network and relates to thecontext and to media files so as to identify at least one media filethat is relevant to the context criteria. Such searches are performedusing the capabilities of the network databases 1320 and theirsupporting infrastructure.

The query module can, without limitation, parse query terms, identifyentities and attributes of entities within the query and furtheridentify relationships between entities and their attributes, as well asrelationships to fixed data, such as times, places, and events. Entitiesand attributes within the query can then be cross referenced against thenetwork databases for correspondence to entities, objects, andattributes within the network database.

In one embodiment, the criteria are interpreted to take advantage thebest available data within the network. For example, if data relevant tothe context resides on a relational database, the query module canexecute a series of SQL statements for retrieving data from a relationaldatabase or a procedural language containing embedded SQL. Queries maybe nested or otherwise constructed to retrieve data from one set ofentities, and to use the result set to drive additional queries againstother entities, or to use recursive data retrieval.

In the case of a W4 COMN, the context request can be stored as an IO.Such an IO may itself be comprised of a cluster of linked IOs relatingto topics, each IO relating to one or more context criteria. In oneembodiment, the query module is a component of a correlation engine of aW4 engine. An IO relating to a context request can be mapped andrepresented against all other known entities and data objects in orderto create both a micro graph for every entity as well as a global graphthat relates all known entities with one another, and media objectsrelevant to the context are thereby identified. In one embodiment, suchrelationships between entities and data objects are stored in a globalindex within the W4 COMN.

Where query criteria relate to simple descriptive matter, such as dateand time of creation, relationships can be identified using metadataembedded in media objects. Where criteria relate to a topic, such as agenre of music, relationships can be identified through IOs (whethercurrently existing or dynamically generated) relating to the topic whichmay then be used to identify media objects associated with the topic.

Where criteria relate to relationships between two or more IOs or RWEs,such as all friends of a particular user, related IOs and RWEs can beidentified using social network relationships supported by the W4 COMN.When a specific media object is selected, the media search module canfurther determine if the user or a user proxy creating the context ispermitted to access the content of the media file using ownership datain or associated with the media object.

Specific Examples of Contexts

The disclosure will now discuss specific examples of the aboveprinciples. The examples given below are intended to be illustrative,and not limiting.

In one example, if a user wished to listen to Motown music of 1967, theuser could enter a context into their media player specifying Motown,music, and 1967. The query engine could search for IOs relating to atopics related to Motown and select media objects associated with thatIO where metadata within related media objects indicates the music wasreleased in 1967. The system would also search for metadata within mediaobjects for “Motown” and “1967.” The resulting playlist would enable theuser to listen to Motown music from 1967.

In another example, if a user loves Manhattan, in one embodiment, theuser could enter a context into their media player specifying music andManhattan. The query engine could search a lyric database, which in oneembodiment is defined to the W4 COMN as a RWE, for music which portraysNew York in a positive light. Additionally or alternatively the queryengine could search for an IO associated with “Manhattan” and selectmedia objects associated with that IO. If no such IO was present, thesystem could search for metadata within media objects for “Manhattan.”

In another example, if a user wished to experience “the summer of love”in San Francisco, in one embodiment, the user could enter a context intotheir media player specifying, for example, either “summer of love” or adate range (the summer of 1967) and a location (San Francisco). If the“summer of love” was entered, the W4 query engine could search for an IOrelated to that topics and select media objects associated with that IO.If no such IO was present, the system could search for metadata withinmedia objects for “summer of love.” If a date range and location wasentered, W4 query engine could search metadata within media objects for“San Francisco” and a date within the specified range. The resultingplaylist would contain music, videos or both that would enable therequester to experience the media of the “summer of love” as if theywere actually experiencing that era.

In another example, if a user is originally from New York City, and nowwishes to listen to the music that was playing during their senior prom,the user would create a context for a year and a place and, possibly agenre, such as popular music, using a W4 interface, for example, a W4URL. The query engine would search W4 databases for media objectsrelated that time and place. For example, the query engine could searchfor publications that publish record charts such as Billboard magazine,or other song or album charting or rating services, e.g. Sound Scan fromthe Nielson Company for the top 40 songs at the time of the user's promand then locate media objects corresponding to those songs. The user canthen listen to the music that would probably have been played at theirsenior prom.

In another example, if a user then wishes to re-experience his collegedays in Los Angeles, the user would create a context specifying hiscollege, a specific year and the group of friends he socialized with atthat time. The query engine could determine from profile, socialnetworking, and interaction data for the user and for any of his friendswho are known to the W4 COMN what kind of music they listen to, whotheir favorite artists are, and what their favorite songs are. The queryengine could then search, for example, using IOs relating to topics andmetadata within media objects for songs by favorite artists for the userand his friends that were released that specific year. The query enginecould further search, for example, metadata within media objects forreferences to the user's college, for Los Angeles, or any of hisfriends. The resulting playlist would contain music, videos or both thatwould enable the requester to experience the media of his college days.

In another example, if a user wished to listen to the favorite music ofsurfers in Hawaii in 1974, the user would create a context specifyingsurfing, Hawaii, and 1974. The query engine could search for users knownto the W4 COMN whose profile or interaction data indicate have surfingas a hobby or interest and who lived in Hawaii in 1974. The musicalpreferences of such users, such as musical genre, favorite artists, orfavorite songs could then be used to search IOs relating to such topicsor metadata within media objects for songs relating to such genre,artists, or songs which were released in 1974. The resulting playlistwould allow the user to experience listen to the music that was probablythe favorite music of surfers in Hawaii in 1974.

In another example, if a user wishes to listen to the favorite music ofpersons who attended (or are attending) a specific concert, the userwould create a context specifying the name, date, and time of theconcert and specifying persons who attended the concert. The queryengine could search the W4 COMN for users whose interaction dataindicates they attended the concert. The musical preferences of suchusers, such as musical genre, favorite artists, or favorite songs couldthen be used to search IOs relating to such topics or metadata withinmedia objects for songs relating to such genre, artists, or songs. Theresulting playlist would contain music, videos or both that would enablethe requester to sample music preferred by persons who attended aspecific concert.

In another example, if a user wishes to create family playlist of thefavorite songs for his family relating to when each of his familymembers was 11 years old, the user would create a context specifying hisfamily, favorite songs, and age 11. The query engine could then searchthe users profile and interaction data to determine who his immediatefamily members are. The query engine would then determine if the usersfamily members are known to the W4 COMN and determine the birthday andmusical preferences of such users, such as musical genre, favoriteartists, or favorite songs. Such preferences could then be used tosearch IOs relating to topics or metadata within media objects for songsrelating to such genre, artists, or songs which fail in a year in whicha specific family member was age 11. The resulting playlist would allowthe user to experience the favorite music of his immediate family whenthey were children.

Real time location data from a users device can also be used to enhancethe user experience. For example, assume a user is currently walkingthrough the Haight Ashbury district of San Francisco with a media playerwhose physical location can be sensed. The user could enter a contextspecifying a specific year and the user's current location. The queryengine could then search W4 databases, for example, using objectmetadata or IOs relating to such topics, for music released in theselected year and relating to (e.g. written or produced in or performedby artists that reside in or resided in) Haight Ashbury or San Franciscoand a playlist relating to that time and place is created. As the userwalks from one area of the city to another, the users device detects thechange in location and changes the context to reflect the user's newlocation. The new context is then use to create a new playlist and adifferent set of music plays that relates to the user's currentlocation. As the user leaves the area and walks or otherwise travelsfurther, the playlist of music may change again to relate to the newlocation.

In an example illustrating the use of the context in an advertisement,advertisers can create ads for modern day products whose music comesfrom another era. For example, an ad for Viagra could be associated witha context whose criteria includes 1958, popular music, and energeticmusic. Such an ad could also be tailored to a user, for example, acontext could be defined containing criteria including the current user,the year the user was 18, and the user's favorite music.

Those skilled in the art will recognize that the methods and systems ofthe present disclosure may be implemented in many manners and as suchare not to be limited by the foregoing exemplary embodiments andexamples. In other words, functional elements being performed by singleor multiple components, in various combinations of hardware and softwareor firmware, and individual functions, may be distributed among softwareapplications at either the client level or server level or both. In thisregard, any number of the features of the different embodimentsdescribed herein may be combined into single or multiple embodiments,and alternate embodiments having fewer than, or more than, all of thefeatures described herein are possible. Functionality may also be, inwhole or in part, distributed among multiple components, in manners nowknown or to become known. Thus, myriad software/hardware/firmwarecombinations are possible in achieving the functions, features,interfaces and preferences described herein. Moreover, the scope of thepresent disclosure covers conventionally known manners for carrying outthe described features and functions and interfaces, as well as thosevariations and modifications that may be made to the hardware orsoftware or firmware components described herein as would be understoodby those skilled in the art now and hereafter.

Furthermore, the embodiments of methods presented and described asflowcharts in this disclosure are provided by way of example in order toprovide a more complete understanding of the technology. The disclosedmethods are not limited to the operations and logical flow presentedherein. Alternative embodiments are contemplated in which the order ofthe various operations is altered and in which sub-operations describedas being part of a larger operation are performed independently.

While various embodiments have been described for purposes of thisdisclosure, such embodiments should not be deemed to limit the teachingof this disclosure to those embodiments. Various changes andmodifications may be made to the elements and operations described aboveto obtain a result that remains within the scope of the systems andprocesses described in this disclosure.

1. A method comprising: receiving a request over a network from arequesting device for media related to a context, the request comprisescontext criteria, the context criteria comprising social, spatial,temporal and topical criteria; formulating a query based on the contextcriteria so as to search, via the network, for user profile data, socialnetwork data, spatial data, temporal data and topical data that isavailable via the network and relates to the context and to media filesso as to identify a plurality of media files that are relevant to thecontext criteria; assembling, via the network, a playlist containing areference to the plurality of media files; and transmitting theplurality of media files on the playlist over the network to therequesting device.
 2. The method of claim 1 wherein the user profiledata comprise data that match a plurality of users, and the preferencesof the plurality of users are used as part of the query.
 3. The methodof claim 1 wherein the social criteria comprise criteria that match aplurality of users within a social network, and the preferences of theplurality of users are used as part of the query.
 4. The method of claim1 wherein the request for media related to a context has a triggercondition and the request is not processed until the trigger conditionoccurs.
 5. The method of claim 4 wherein the trigger condition isselected from the group consisting of a time, a date, a calendar event,the presence of the requesting device in a physical location, display ofan advertisement on the requesting device, selection of an advertisementon the requesting device.
 6. The method of claim 1 wherein the requestis transmitted from the requesting device when an advertisement isdisplayed or selected on the requesting device.
 7. The method of claim 1further comprising: detecting a change via the network in the physicallocation of the requesting device over the network, wherein the contextcriteria specifies the physical location of the requesting device;formulating a second query based on the context criteria so as tosearch, via the network, for user profile data, social network data,spatial data, temporal data and topical data that is available via thenetwork and relates to the context and to media files so as to identifya second plurality of media files that are relevant to the contextcriteria, wherein the context criteria reflect the change in thephysical location; and assembling via the network an altered playlistcontaining a reference to the second plurality of media files;transmitting the second plurality of media files on the altered playlistover the network to the requesting device.
 8. A system comprising: aprocessor; a storage medium for tangibly storing thereon program logicfor execution by the processor, the program logic comprising: logicexecuted by the processor for receiving a request over a network from arequesting device associated for media related to a context, wherein therequest comprises context criteria, the context criteria comprisingsocial, spatial, temporal and topical criteria; logic executed by theprocessor for formulating a query based on the context criteria so as tosearch, via the network, for user profile data, social network data,spatial data, temporal data and topical data that is available via thenetwork and relates to the context and to media files so as to identifya plurality of media files that are relevant to the context criteria;logic executed by the processor for assembling via the network aplaylist containing a reference to the plurality of media files; andlogic executed by the processor for transmitting the plurality of mediafiles on the playlist over the network to the requesting device.
 9. Thesystem of claim 8 wherein the user profile data comprise data that matcha plurality of users, and the preferences of the plurality of users areused as part of the query.
 10. The system of claim 8 wherein the socialcriteria comprise criteria that match a plurality of users within asocial network, and the preferences of the plurality of users are usedas part of the query.
 11. The system of claim 8 wherein the request formedia related to a context has a trigger condition and the request isnot processed until the trigger condition occurs, wherein the triggercondition is selected from the list: a time, a date, a calendar event,the presence of the requesting device in a physical location, display ofan advertisement on the requesting device, selection of an advertisementon the requesting device.
 12. (canceled)
 13. The system of claim 8wherein the request is transmitted from the requesting device when anadvertisement is displayed or selected on the requesting device.
 14. Thesystem of claim 8 wherein the context criteria specifies the physicallocation of the requesting device, and if the physical location of therequesting device changes, the program logic further comprises: logicexecuted by the processor for detecting a change via the network in thephysical location of the requesting device over the network, wherein thecontext criteria specifies the physical location of the requestingdevice; logic executed by the processor for formulating a second querybased on the context criteria so as to search, via the network, for userprofile data, social network data, spatial data, temporal data andtopical data that is available via the network and relates to thecontext and to media files so as to identify a second plurality of mediafiles that are relevant to the context criteria, wherein the contextcriteria reflect the change in the physical location; logic executed bythe processor for assembling via the network an altered playlistcontaining a reference to the second plurality of media files; and logicexecuted by the processor for transmitting the second plurality of atleast one media files on the altered playlist over the network to therequesting device.
 15. A non-transitory computer-readable storage mediumtangibly encoded with computer-executable instructions, that whenexecuted by a computing device, perform a method comprising: receiving arequest over a network from a requesting device associated for mediarelated to a context, wherein the request comprises context criteria,the context query comprising social, spatial, temporal and topicalcriteria; formulating a query based on the context criteria so as tosearch, via the network, for user profile data, social network data,spatial data, temporal data and topical data that is available via thenetwork and relates to the context and to media files so as to identifya plurality of media files that are relevant to the context criteria;assembling, via the network, a playlist containing a reference to theplurality of media files; and transmitting the plurality of media fileson the playlist over the network to the requesting device.
 16. Thenon-transitory computer-readable storage medium of claim 15 wherein theuser profile data comprise data that match a plurality of users, and thepreferences of the plurality of users are used as part of the query. 17.The non-transitory computer-readable storage medium of claim 15 whereinthe social criteria comprise criteria that match a plurality of userswithin a social network, and the preferences of the plurality of usersare used as part of the query.
 18. The non-transitory computer-readablestorage medium of claim 15 wherein the request for media related to acontext has a trigger condition and the request is not processed untilthe trigger condition occurs, wherein the trigger condition is selectedfrom the group consisting of a time, a date, a calendar event, thepresence of the requesting device in a physical location, display of anadvertisement on the requesting device, selection of an advertisement onthe requesting device.
 19. (canceled)
 20. The non-transitorycomputer-readable storage medium of claim 15 wherein the request istransmitted from the requesting device when an advertisement isdisplayed or selected on the requesting device.
 21. The non-transitorycomputer-readable storage medium of claim 15 further comprising:detecting a change via the network in the physical location of therequesting device over the network, wherein the context criteriaspecifies the physical location of the requesting device; formulate asecond query based on the context criteria so as to search, via thenetwork, for user profile data, social network data, spatial data,temporal data and topical data that is available via the network andrelates to the context and to media files so as to identify a secondplurality of media files that are relevant to the context criteria,wherein the context criteria reflect the change in the physicallocation; assembling via the network an altered playlist containing areference to the second plurality of media files; and transmitting thesecond plurality of media files on the altered playlist over the networkto the requesting device.